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Tier-1 brand and metro location increase competition, but senior specialized ML focus reduces applicant density.
Advanced ML techniques and healthcare domain preference make skills less transferable across industries.
Explicit 8+ years, deep ML stack and production deployment requirements create strict filters.
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Lead development of advanced ML and statistical models addressing complex healthcare problems, focusing on healthcare revenue cycle domain.
Establish best practices in modeling, experimentation, and analytical rigor while converting healthcare challenges into scalable data science solutions.
Collaborate with global stakeholders to influence product and business strategy and mentor the data science team to enhance technical capabilities.
8+ years of experience in data science or related quantitative field (e.g., Computer Science, Statistics, Mathematics).
Bachelor of Engineering degree mandatory.
Experience with advanced ML techniques including Transformers, Deep Learning, Graph Neural Networks, and handling large high-dimensional datasets.
Prior experience or domain knowledge in healthcare, preferably healthcare revenue cycle.
Experienced in deploying ML models into production environments within healthcare.
Proficient in modern machine learning and statistical modeling methods, comfortable with ambiguous problems and independent outcome delivery.
Able to communicate effectively with diverse stakeholders and mentor technical teams in a complex data analytics environment.